CSpace

Browse/Search Results:  1-10 of 36 Help

Selected(0)Clear Items/Page:    Sort:
VPNets: Volume-preserving neural networks for learning source-free dynamics 期刊论文
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2022, 卷号: 416, 页码: 12
Authors:  Zhu, Aiqing;  Zhu, Beibei;  Zhang, Jiawei;  Tang, Yifa;  Liu, Jian
Favorite  |  View/Download:47/0  |  Submit date:2023/02/07
Deep learning  Neural networks  Discovery of dynamics  Source-free dynamics  Volume-preserving  
Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator 期刊论文
CHAOS SOLITONS & FRACTALS, 2022, 卷号: 165, 页码: 14
Authors:  Zhong, Ming;  Yan, Zhenya
Favorite  |  View/Download:46/0  |  Submit date:2023/02/07
Integrable fractional nonlinear wave equations  Fourier neural operator  Deep learning  Data-driven soliton mapping  Activation function  Channel of fully-connected layer  
Deep graph level anomaly detection with contrastive learning 期刊论文
SCIENTIFIC REPORTS, 2022, 卷号: 12, 期号: 1, 页码: 11
Authors:  Luo, Xuexiong;  Wu, Jia;  Yang, Jian;  Xue, Shan;  Peng, Hao;  Zhou, Chuan;  Chen, Hongyang;  Li, Zhao;  Sheng, Quan Z.
Favorite  |  View/Download:56/0  |  Submit date:2023/02/07
Data-driven rogue waves and parameters discovery in nearly integrable PT-symmetric Gross-Pitaevskii equations via PINNs deep learning 期刊论文
PHYSICA D-NONLINEAR PHENOMENA, 2022, 卷号: 439, 页码: 12
Authors:  Zhong, Ming;  Gong, Shibo;  Tian, Shou-Fu;  Yan, Zhenya
Favorite  |  View/Download:48/0  |  Submit date:2023/02/07
GeneralizedGrossPitaevskiiequation  ComplexPT-symmetricpotentials  Physics-informeddeepneuralnetworks  Data-driven rogue waves and parameters discovery discovery  
Data-driven discoveries of B?cklund transformations and soliton evolution equations via deep neural network learning schemes 期刊论文
PHYSICS LETTERS A, 2022, 卷号: 450, 页码: 15
Authors:  Zhou, Zijian;  Wang, Li;  Yan, Zhenya
Favorite  |  View/Download:58/0  |  Submit date:2023/02/07
Deep neural networks  B?cklund transform  Miura transform  Soliton equations  Breathers  Solitons  
DRVN (deep random vortex network): A new physics-informed machine learning method for simulating and inferring incompressible fluid flows 期刊论文
PHYSICS OF FLUIDS, 2022, 卷号: 34, 期号: 10, 页码: 21
Authors:  Zhang, Rui;  Hu, Peiyan;  Meng, Qi;  Wang, Yue;  Zhu, Rongchan;  Chen, Bingguang;  Ma, Zhi-Ming;  Liu, Tie-Yan
Favorite  |  View/Download:49/0  |  Submit date:2023/02/07
Monte Carlo fPINNs: Deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 卷号: 400, 页码: 17
Authors:  Guo, Ling;  Wu, Hao;  Yu, Xiaochen;  Zhou, Tao
Favorite  |  View/Download:36/0  |  Submit date:2023/02/07
Physics -informed neural networks  Fractional Laplacian  Nonlocal operators  Uncertainty quantification  
Networked Knowledge and Complex Networks: An Engineering View 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 8, 页码: 1366-1383
Authors:  Lu, Jinhu;  Wen, Guanghui;  Lu, Ruqian;  Wang, Yong;  Zhang, Songmao
Favorite  |  View/Download:76/0  |  Submit date:2023/02/07
Complex network  knowledge graph  networked knowledge  neural network  
Data-Driven Deep Learning for The Multi-Hump Solitons and Parameters Discovery in NLS Equations with Generalized PT-Scarf-II Potentials 期刊论文
NEURAL PROCESSING LETTERS, 2022, 页码: 19
Authors:  Zhong, Ming;  Zhang, Jian-Guo;  Zhou, Zijian;  Tian, Shou-Fu;  Yan, Zhenya
Favorite  |  View/Download:39/0  |  Submit date:2023/02/07
Focusing and defocusing nonlinear Schrodinger equations  Generalized PT-Scarf-II potential  Physics-informed deep neural networks  Data-driven solitons and parameters discovery  
eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks 期刊论文
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2022, 卷号: 40, 期号: 3, 页码: 29
Authors:  Zhang, Ge;  Li, Zhao;  Huang, Jiaming;  Wu, Jia;  Zhou, Chuan;  Yang, Jian;  Gao, Jianliang
Favorite  |  View/Download:177/0  |  Submit date:2022/04/29
Online e-commerce platforms  fraud detection system  graph neural networks